PERSPECTIVE Complexity of the Basic Reproduction Number (R0) Paul L. Delamater, Erica J. Street, Timothy F. Leslie, Y. Tony Yang, Kathryn H. Jacobsen The basic reproduction number (R0), also called the basic The concept of R0 was first introduced in the field reproduction ratio or rate or the basic reproductive rate, of demography (9), where this metric was used to count is an epidemiologic metric used to describe the conta- offspring. When 0R was adopted for use by epidemiologists, giousness or transmissibility of infectious agents. R is 0 the objects being counted were infective cases (19). Numer- affected by numerous biological, sociobehavioral, and ous definitions for R have been proposed. Although the ba- environmental factors that govern pathogen transmission 0 sic conceptual framework is similar for each, the operational and, therefore, is usually estimated with various types of definitions are not always identical. Dietz states that R is “the complex mathematical models, which make R easily mis- 0 0 number of secondary cases one case would produce in a com- represented, misinterpreted, and misapplied. R0 is not a biological constant for a pathogen, a rate over time, or a pletely susceptible population” (19). Fine supplements this definition with the description “average number of second- measure of disease severity, and R0 cannot be modified through vaccination campaigns. R0 is rarely measured di- ary cases” (17). Diekmann and colleagues use the description rectly, and modeled R0 values are dependent on model “expected number of secondary cases” and provide addition- structures and assumptions. Some R0 values reported in al specificity to the terminology regarding a single case 13( ). the scientific literature are likely obsolete. R must be es- 0 In the hands of experts, R0 can be a valuable concept. timated, reported, and applied with great caution because However, the process of defining, calculating, interpreting, this basic metric is far from simple. and applying R0 is far from straightforward. The simplicity of an R0 value and its corresponding interpretation in relation to infectious disease dynamics masks the complicated nature of he basic reproduction number (R0), pronounced “R this metric. Although R is a biological reality, this value is Tnaught,” is intended to be an indicator of the conta- 0 giousness or transmissibility of infectious and parasitic usually estimated with complex mathematical models devel- oped using various sets of assumptions. The interpretation of agents. R0 is often encountered in the epidemiology and public health literature and can also be found in the popu- R0 estimates derived from different models requires an under- standing of the models’ structures, inputs, and interactions. lar press (1–6). R0 has been described as being one of the fundamental and most often used metrics for the study of Because many researchers using R0 have not been trained in sophisticated mathematical techniques, R is easily subject infectious disease dynamics (7–12). An R0 for an infectious 0 disease event is generally reported as a single numeric to misrepresentation, misinterpretation, and misapplication. value or low–high range, and the interpretation is typically Notable examples include incorrectly defining 0R (1) and presented as straightforward; an outbreak is expected to misinterpreting the effects of vaccination on 0R (3). Further, many past lessons regarding this metric appear to have been continue if R0 has a value >1 and to end if R0 is <1 (13). The potential size of an outbreak or epidemic often is based lost or overlooked over time. Therefore, a review of the con- cept of R is needed, given the increased attention this metric on the magnitude of the R0 value for that event (10), and 0 receives in the academic literature (20). In this article, we ad- R0 can be used to estimate the proportion of the popula- tion that must be vaccinated to eliminate an infection from dress misconceptions about R0 that have proliferated as this metric has become more frequently used outside of the realm that population (14,15). R0 values have been published for measles, polio, influenza, Ebola virus disease, HIV disease, of mathematical biology and theoretic epidemiology, and we a diversity of vectorborne infectious diseases, and many recommend that R0 be applied and discussed with caution. other communicable diseases (14,16–18). Variations in R0 Affiliations: University of North Carolina at Chapel Hill, Chapel Hill, For any given infectious agent, the scientific literature North Carolina, USA (P.L. Delamater); George Mason University, might present numerous different 0R values. Estimations of Fairfax, Virginia, USA (E.J. Street, T.F. Leslie, K.H. Jacobsen); the R0 value are often calculated as a function of 3 primary George Washington University, Washington, DC, USA (Y.T. Yang) parameters—the duration of contagiousness after a person becomes infected, the likelihood of infection per contact DOI: https://doi.org/10.3201/eid2501.171901 between a susceptible person and an infectious person or Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 25, No. 1, January 2019 1 PERSPECTIVE vector, and the contact rate—along with additional param- disease produced by the infection is severe. Instead, R0 is eters that can be added to describe more complex cycles of most accurately described in terms of cases per case (7,13). transmission (19). Further, the epidemiologic triad (agent, Calling R0 a rate rather than a number or ratio might create host, and environmental factors) sometimes provides in- some undue confusion about what the value represents. spiration for adding parameters related to the availability of public health resources, the policy environment, various R0 and Vaccination Campaigns aspects of the built environment, and other factors that in- Vaccination campaigns reduce the proportion of a popula- fluence transmission dynamics and, thus, are relevant for tion at risk for infection and have proven to be highly ef- the estimation of R0 values (21). Yet, even if the infectious- fective in mitigating future outbreaks (26). This conclusion ness of a pathogen (that is, the likelihood of infection oc- is sometimes used to suggest that an aim of vaccination curring after an effective contact event has occurred) and campaigns is to remove susceptible members of the popu- the duration of contagiousness are biological constants, R0 lation to reduce the R0 for the event to <1. Although the will fluctuate if the rate of human–human or human–vec- removal of susceptible members from the population will tor interactions varies over time or space. Limited evidence affect infection transmission by reducing the number of supports the applicability of R0 outside the region where effective contacts between infectious and susceptible per- the value was calculated (20). Any factor having the po- sons, this activity will technically not reduce the R0 value tential to influence the contact rate, including population because the definition of 0R includes the assumption of a density (e.g., rural vs. urban), social organization (e.g., in- completely susceptible population. When examining the tegrated vs. segregated), and seasonality (e.g., wet vs. rainy effect of vaccination, the more appropriate metric to use is season for vectorborne infections), will ultimately affect the effective reproduction number (R), which is similar to R0. Because R0 is a function of the effective contact rate, R0 but does not assume complete susceptibility of the pop- the value of R0 is a function of human social behavior and ulation and, therefore, can be estimated with populations organization, as well as the innate biological characteristics having immune members (16,20,27). Efforts aimed at re- of particular pathogens. More than 20 different R0 values ducing the number of susceptible persons within a popula- (range 5.4–18) were reported for measles in a variety of tion through vaccination would result in a reduction of the study areas and periods (22), and a review in 2017 iden- R value, rather than R0 value. In this scenario, vaccination tified feasible measles 0R values of 3.7–203.3 (23). This could potentially end an epidemic, if R can be reduced to wide range highlights the potential variability in the value a value <1 (16,27,28). The effective reproduction number of R0 for an infectious disease event on the basis of local can also be specified at a particular timet , presented as R(t) sociobehavioral and environmental circumstances. or Rt, which can be used to trace changes in R as the number of susceptible members in a population is reduced (29,30). Various Names for R0 When the goal is to measure the effectiveness of vaccina- Inconsistency in the name and definition of 0R has potential- tion campaigns or other public health interventions, R0 is ly been a cause for misunderstanding the meaning of R0. R0 not necessarily the best metric (10,20). was originally called the basic case reproduction rate when George MacDonald introduced the concept into the epi- Measuring and Estimating R0 demiology literature in the 1950s (17,19,24,25). Although Counting the number of cases of infection during an epi- MacDonald used Z0 to represent the metric, the current sym- demic can be extremely difficult, even when public health bolic representation (R0) appears to have remained largely officials use active surveillance and contact tracing to at- consistent since that time. However, multiple variations of tempt to locate all infected persons. Although measuring the name for the concept expressed by R0 have been used in the true R0 value is possible during an outbreak of a newly the scientific literature, including the use of basic and case emerging infectious pathogen that is spreading through a as the first word in the term, reproduction and reproductive wholly susceptible population, rarely are there sufficient for the second word, and number, ratio, and rate for the final data collection systems in place to capture the early stages part of the term (13).